Digital photography has become ubiquitous. Image blur is very common in natural photos, arising from different factors such as object motion, camera lens out-of-focus issues, and camera shake. In many cases, blur is undesired when important regions are affected and become less sharp. However, in other cases, blur may actually be desired, for example, when the background is blurred to make the subject pop out, or motion blur is added to give the photo an artistic look.
Many research efforts have focused on detection of undesired blur, its removal or direct estimation of desired blur, and its enhancement. However, there have been no or otherwise unknown efforts to develop an algorithm to programmatically understand whether blur is desired or not in the first place. Classifying blur as desirable or undesirable would be very useful, for instance, to help users categorize photos and make corresponding edits, especially with the dramatic growth in the number of personal photos. Blur analysis can also be used to estimate photo quality, as well as be applied in photo curation, photo collage creation, and video summarization.
As previously noted, images may have areas of blurriness due to various factors, with some occurrences of blur being desirable and others undesirable. For example, two photos may utilize a depth-of-field effect. One photo may be regarded as good or acceptable while the other may be considered bad or unacceptable due to the particular elements of content that are blurry. Similarly, a photo may be considered of in-between quality depending upon which content in the image is blurry and the particularities of the blurriness. For example, a photo of a tennis player may be considered of poor quality if the intended or agreed-upon subject is blurry. As an additional example, a photo with a shallow depth-of-field effect can be desirable if the subject is highlighted in the background. However, it can be undesirable if the main subject is out of focus (i.e., the main subject is blurry).
Thus, whether blur is desirable or undesirable depends on the content that is blurred in context with the rest of the photograph. It is desirable to evaluate the blur characteristics inherent in particular images in automated programmatic fashion so that digital photographs may be categorized. However, performing blur desirability classification is not trivial. For instance, successfully performing blur classification requires not only accurate spatially varying blur amount estimation but also an understanding whether the blurry regions are important from the perspective of image content and the photographer's intent (e.g., an image having blur in the face of a tennis player that has just struck a tennis ball will likely be undesirable, while blur of the struck ball captured in that same image may actually be desired).